Biology subjects

Bestmann, S.

Publications and source records attributed to Bestmann, S..

34 records · Page 2Linked to original sources

bioRxiv2021

The impact of brain lesions on tDCS-induced electric field magnitude

BackgroundTranscranial direct current stimulation (tDCS) has been used to enhance motor and language rehabilitation following a stroke. However, improving the effectiveness of clinical tDCS protocols depends on understanding how lesions may influence tDCS-induced current flow through the brain. ObjectiveWe systematically investigated the effect of brain lesions on the magnitude of electric fields (e-mag) induced by tDCS, and how to overcome lesion-induced inter-individual variability in e-mag. MethodsWe simulated the effect of 630 different lesions - by varying lesion location, distance from the target region of interest (ROI), size and conductivity - on tDCS-induced e-mag in the brains of two participants. Current flow modelling was conducted for two tDCS montages commonly used in clinical applications, which target either primary motor cortex (M1) or Brocas area (BA44), respectively. We further explored how the inherent variability in e-mag that is introduced by inter-lesion differences can be overcome by individualising tDCS protocols. ResultsThe effect on absolute e-mag was highly dependent on lesion size, conductance and the distance from the target ROI. Larger lesions, with high conductivity, closer to the ROI caused e-mag changes of more than 30%. The sign of this change was determined by the location of the lesion. Specifically, lesions located in-line with the predominant direction of current flow increased e-mag in the ROI, whereas lesions located in the opposite direction caused a decrease. Lesions had a large impact on the optimal electrode configuration if attempting to maximise for the total e-mag in the ROI, but little impact if only the component of e-mag flowing radially inward to the cortex was maximised. Knowing the effect of a given lesion on e-mag also allows for individualising tDCS intensity to reduce variability. ConclusionsThese results demonstrate that tDCS-induced electric fields are profoundly influenced by lesion characteristics, and further exacerbate the known variability in e-mag across individuals. Additionally, the dependence of these results on the assigned conductance of the lesion underlines the need for improved estimates of lesion conductivity for current flow models. Our results highlight the need for individualised dose control of tDCS in the lesioned brain to overcome the substantial inter-individual variability in electric fields delivered to a cortical target region. Highlights- Lesions can alter tDCS-induced electric field magnitude (e-mag) in a target by 30% - Lesions can cause increases or decreases to e-mag - Direction of change depends on the position of the lesion relative to current flow - Lesion conductivity - the true value for which is unknown - also impacts change - E-mag variability can be reduced by individualising montage and stimulation intensity

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bioRxiv2021

Laminar dynamics of beta bursts in human motor cortex

Modulation of motor cortical activity in the beta frequency range is one of the strongest and most studied movement-related neural signals. At the single trial level, beta band activity is often characterized by transient bursting events rather than slowly modulating oscillations, suggesting a more rapid, information-encoding functional role than previously believed. Insight into how beta bursts are generated in sensorimotor circuits can provide important constraints to theories about their functional role for movement control. To this end, we leverage and extend recent developments in high precision MEG for temporally resolved laminar analysis of burst activity, combined with a neocortical circuit model that simulates the biophysical generators of the electrical currents which drive beta bursts. This approach pinpoints the generation of beta bursts in human motor cortex to distinct excitatory synaptic inputs to deep and superficial cortical layers, which drive current flow in opposite directions. These laminar dynamics of beta bursts in motor cortex align with prior invasive animal recordings within the somatosensory cortex, and suggest a conserved mechanism for somatosensory and motor cortical beta bursts. More generally, we demonstrate the ability for uncovering the laminar dynamics of event-related neural signals in human non-invasive recordings.

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bioRxiv2020

Dynamic causal modeling of layered magnetoencephalographic event-related responses

The layered architecture of cortex is thought to play a fundamental role in shaping cortical computations. However, direct electrophysiological measurements of layered activity are not possible non-invasively in humans. Recent advances have shown that a distinction of two layers can be achieved using magnetoencephalography in combination with head casts and advanced spatial modeling. In this technical note, we present a dynamic causal model of a single cortical microcircuit that models event related potentials. The model captures the average dynamics of a detailed two layered circuit. It combines a temporal model of neural dynamics with a spatial model of a layer specific lead field to facilitate layer separation. In simulations we show that the spatial arrangement of the two layers can be successfully recovered using Bayesian inference. The layered model can also be distinguished from a single dipole model. We conclude that precision magnetoencephalography in combination with detailed dynamical system modeling can be used to study non-invasively the fast dynamics of layered computations.

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bioRxiv2020

Mouth magnetoencephalography: A unique perspective on the human hippocampus

Traditional magnetoencephalographic (MEG) brain imaging scanners consist of a rigid sensor array surrounding the head; this means that they are maximally sensitive to superficial brain structures. New technology based on optical pumping means that we can now consider more flexible and creative sensor placement. Here we explored the magnetic fields generated by a model of the human hippocampus not only across scalp but also at the roof of the mouth. We found that simulated hippocampal sources gave rise to dipolar field patterns with one scalp surface field extremum at the temporal lobe and a corresponding maximum or minimum at the roof of the mouth. We then constructed a fitted dental mould to accommodate an Optically Pumped Magnetometer (OPM). We collected data using a previously validated hippocampal-dependent task to test the empirical utility of a mouth-based sensor, with an accompanying array of left and right temporal lobe OPMs. We found that the mouth sensor showed the greatest task-related theta power change. We also found that, as predicted by the simulations, the mouth sensor was anti-correlated with those on over the temporal lobes. We found that this sensor had a mild effect on the reconstructed power in the hippocampus (~10% change) but that coherence images between the mouth sensor and reconstructed source images showed a global maximum in the right hippocampus. We conclude that augmenting a scalp-based MEG array with sensors in the mouth shows unique promise for both basic scientists and clinicians interested in interrogating the hippocampus.

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bioRxiv2019

Increasing motor skill acquisition by driving theta-gamma coupling

Skill learning is a fundamental adaptive process, but the mechanisms remain poorly understood. Hippocampal learning is closely associated with gamma activity, which is amplitude-modulated by the phase of underlying theta activity. Whether such nested activity patterns also underpin skill acquisition in non-hippocampal tasks is unknown. Here we addressed this question by using transcranial alternating current stimulation (tACS) over sensorimotor cortex to modulate theta-gamma activity during motor skill acquisition, as an exemplar of a non-hippocampal-dependent task. We demonstrated, and then replicated, a significant improvement in skill acquisition with theta-gamma tACS, which outlasted the stimulation by an hour. Our results suggest that theta-gamma activity may be a common mechanism for learning across the brain and provides a putative novel intervention for optimising functional improvements in response to training or therapy.

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bioRxiv2019

Estimates of cortical column orientation improveMEG source inversion

Determining the anatomical source of brain activity non-invasively measured from EEG or MEG sensors is challenging. In order to simplify the source localization problem, many techniques introduce the assumption that current sources lie on the cortical surface. Another common assumption is that this current flow is orthogonal to the cortical surface, thereby approximating the orientation of cortical columns. However, it is not clear which cortical surface to use to define the current source locations, and normal vectors computed from a single cortical surface may not be the best approximation to the orientation of cortical columns. We compared three different surface location priors and five different approaches for estimating dipole vector orientation, both in simulations and visual and motor evoked MEG responses. We show that models with source locations on the white matter surface and using methods based on establishing correspondences between white matter and pial cortical surfaces dramatically outperform models with source locations on the pial or combined pial/white surfaces and which use methods based on the geometry of a single cortical surface in fitting evoked visual and motor responses. These methods can be easily implemented and adopted in most M/EEG analysis pipelines, with the potential to significantly improve source localization of evoked responses.

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bioRxiv2019

Dose-controlled tDCS reduces electric field intensity variability at a cortical target site

BackgroundVariable effects limit the efficacy of transcranial direct current stimulation (tDCS) as a research and therapeutic tool. Conventional application of a fixed-dose of tDCS does not account for inter-individual differences in anatomy (e.g. skull thickness), which varies the amount of current reaching the brain. Individualised dose-control may reduce the variable effects of tDCS by reducing variability in electric field intensities at a cortical target site.\n\nObjectiveTo characterise the variability in electric field intensity at a cortical site (left primary motor cortex; M1) and throughout the brain for conventional fixed-dose tDCS, and individualised dose-controlled tDCS.\n\nMethodsThe intensity and distribution of the electric field during tDCS was estimated using Realistic Volumetric Approach to Simulate Transcranial Electric Stimulation (ROAST) in 50 individual brain scans taken from the Human Connectome Project, for fixed-dose tDCS (1mA & 2mA) and individualised dose-controlled tDCS targeting left M1.\n\nResultsWith a fixed-dose (1mA & 2mA), E-field intensity in left M1 varied by more than 100% across individuals, with substantial variation observed throughout the brain as well. Individualised dose-controlled ensured the same E-field intensity was delivered to left M1 in all individuals. Its variance in other regions of interest (right M1 and area underneath the electrodes) was comparable with fixed- and individualised-dose.\n\nConclusionsIndividualized dose-control can eliminate the variance in electric field intensities at a cortical target site. Assuming that the current delivered to the brain directly determines its physiological and behavioural consequences, this approach may allow for reducing the known variability of tDCS effects.

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bioRxiv2018

Using optically-pumped magnetometers to measure magnetoencephalographic signals in the human cerebellum

We test the feasibility of an optically pumped magnetometer (OPM)-MEG system for the measurement of human cerebellar activity. We show that the OPM system allows for excellent coverage of this structure by decreasing the average sensor-to-cerebellum distance by around 33% (16mm), compared to a standard MEG helmet. This closer proximity to the cerebellum approximately doubles the signal-to-noise ratio (SNR). As a proof of principle, we used an air-puff stimulus to the eyeball in order to elicit cerebellar evoked and induced responses that are well characterized in non-human models. In three subjects, we observed an evoked component at 50ms post stimulus, which originates in the cerebellum (predominantly ipsilateral). This response was followed by a second component at 100ms post stimulus (predominantly contra-lateral). Sensory stimulation also elicited an event-related broadband spectral power change in the ipsilateral cerebellum at ~100ms in all subjects. We conclude that the OPM-MEG technology offers a promising way to advance the understanding of the information processing mechanisms in the human cerebellum.

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bioRxiv2018

Motor cortical beta transients delay movement initiation and track errors

Motor cortical activity in the beta range (13-30 Hz) is a hallmark signature of healthy and pathological movement, but its behavioural relevance remains unclear. Recent work in primates and human sensory cortex suggests that sustained oscillatory beta activity observed on average, may arise from the summation of underlying short-lasting, high-amplitude bursts of activity. Classical human movement-related event-related beta desynchronisation (ERD) and synchronization (ERS) may thus provide insufficient, non-dynamic, summaries of underlying focal spatio-temporal burst activity, limiting insight into their functional role during healthy and pathological movement.\n\nHere we directly investigate this transient beta burst activity and its putative behavioural relevance for movement control, using high-precision magnetoencephalography (MEG). We quantified the subject-specific (n=8), trial-wise (n>12,000) dynamics of beta bursts, before and after movement. We show that beta activity on individual trials is dominated by high amplitude, short lasting bursts. While average beta changes generally manifest as bilaterally distributed activity (FWHM = 25mm), individual bursts are spatially more focal (FWHM = 6 mm), sporadic (1.3 -1.5/s), and transient (mean: 96 ms).\n\nPrior to movement (the period of the classical ERD), the timing of the last pre-movement burst predicts movement onset, suggesting a role in the specification of the goal of movement. After movement (the period of the classical ERS), the first beta burst is delayed by ~100ms after a response error occurs, intimating a role in error monitoring and evaluation.\n\nMovement-related beta activity is therefore dominated by a spatially dispersed summation of short lasting, sporadic and focal bursts. Movement-related beta bursts coordinate the retrieval and updating of movement goals in the pre- and post-movement periods, respectively.

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bioRxiv2018

Quantifying the performance of MEG source reconstruction using resting state data

Resting state networks measured with magnetoencephalography (MEG) form transiently stable spatio-temporal patterns in the subsecond range, and therefore fluctuate more rapidly than previously appreciated. These states populate and interact across the whole brain, are simple to record, and possess the same dynamic structure of task related changes. They therefore provide a generic, heterogeneous, and plentiful functional substrate against which to test different MEG recording and reconstruction approaches. Here we validate a non-invasive method for quantifying the resolution of different inversion assumptions under different recording regimes (with and without head-casts) based on resting state MEG. Spatio-temporally partitioning of data into self-similar periods confirmed a rich and rapidly dynamic temporal structure with a small number of regularly reoccurring states. To test the anatomical precision that could be resolved through these transient states we then inverted these data onto libraries of systematically distorted, subject specific, cortical meshes and compared the quality of the fit using Cross Validation and a Free Energy metric. This revealed which inversion scheme was able to best support the least distorted (most accurate) anatomical models. Both datasets showed an increase in model fit as anatomical models moved towards the true cortical surface. In the head-cast MEG data, the Empirical Bayesian Beamformer (EBB) algorithm showed the best mean anatomical discrimination (3.7 mm) compared with Minimum Norm / LORETA (6.0 mm) and Multiple Sparse priors (9.4 mm). This pattern was replicated in the second (conventional dataset) although with a marginally poorer prediction of the missing (cross-validated) data. Our findings suggest that the abundant resting state data now commonly available could be used to refine and validate MEG source reconstruction methods or recording paradigms.

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bioRxiv2017

Laminar-specific cortical dynamics in human visual and sensorimotor cortices

Lower frequency, feedback, activity in the alpha and beta range is thought to predominantly originate from infragranular cortical layers, whereas feedforward signals in the gamma range stem largely from supragranular layers. Distinct anatomical and spectral channels may therefore play specialized roles in communication within hierarchical cortical networks; however, empirical evidence for this organization in humans is limited. We leverage high precision MEG to test this proposal, directly and non-invasively, in human participants during visually guided actions. Visual alpha activity mapped onto deep cortical laminae, whereas visual gamma activity predominantly arose from superficial laminae. This laminar-specificity was echoed in sensorimotor beta and gamma activity. Visual gamma activity scaled with task demands in a way compatible with feedforward signaling. For sensorimotor activity, we observed a more complex relationship with feedback and feedforward processes. Distinct frequency channels thus operate in a laminar-specific manner, but with dissociable functional roles across sensory and motor cortices.

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bioRxiv2017

Action boosts episodic memory encoding in humans via engagement of a noradrenergic system.

We are constantly interacting with our environment whilst we encode memories. However, how actions influence memory formation remains poorly understood. Goal-directed movement engages the locus coeruleus (LC), the main source of noradrenaline in the brain. Noradrenaline is also known to enhance episodic encoding, suggesting that action could improve memory via LC engagement. Here we demonstrate, across seven experiments, that action (Go-response) enhances episodic encoding for stimuli unrelated to the action itself, compared to action inhibition (NoGo). Supporting a noradrenergic mechanism underlying this enhancement, functional magnetic resonance imaging, and pupil diameter as a proxy measure for LC-noradrenaline transmission, indicate increased encoding-related LC activity during action. A final experiment confirmed a novel prediction derived from these data that emotionally aversive stimuli, which recruit the noradrenergic system, modulate the mnemonic advantage conferred by Go-responses relative to neutral stimuli. We therefore provide converging evidence that action boosts episodic memory encoding via a noradrenergic mechanism.

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bioRxiv2017

Age-dependent Pavlovian biases influence motor decision-making

Healthy ageing is associated with decreased risk taking in motor1 and economic2-4 decision-making. However, it is unknown whether a single underlying mechanism explains these changes. Age-related changes in economic risk taking are explained by reduced Pavlovian biases that promote action toward reward2, 5, 6. Although Pavlovian biases also promote inaction in the face of punishment, the role such Pavlovian biases play in motor decision-making, which additionally depends on estimating the probability of successfully executing an action7-10, is unknown. To address this, we developed a novel app-based motor decision-making task to measure sensitivity to reward and punishment when subjects (n=26,532) made a go/no-go motor gamble based on the perceived ability to execut ...

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bioRxiv2017

tDCS changes in motor excitability are specific to orientation of current flow

Measurements and models of current flow in the brain during transcranial Direct Current Stimulation (tDCS) indicate stimulation of regions in-between electrodes. Moreover, the cephalic cortex result in local fluctuations in current flow intensity and direction, and animal studies suggest current flow direction relative to cortical columns determines response to tDCS. Here we test this idea by measuring changes in cortico-spinal excitability by Transcranial Magnetic Stimulation Motor Evoked Potentials (TMS-MEP), following tDCS applied with electrodes aligned orthogonal (across) or parallel to M1 in the central sulcus. Current flow models predicted that the orthogonal electrode montage produces consistently oriented current across the hand region of M1 that flows along cortical columns, while the parallel electrode montage produces none-uniform current directions across the M1 cortical surface. We find that orthogonal, but not parallel, orientated tDCS modulates TMS-MEPs. We also show modulation is sensitive to the orientation of the TMS coil (PA or AP), which is through to select different afferent pathways to M1. Our results are consistent with tDCS producing directionally specific neuromodulation in brain regions in-between electrodes, but shows nuanced changes in excitability that are presumably current direction relative to column and axon pathway specific. We suggest that the direction of current flow through cortical target regions should be considered for targeting and dose-control of tDCS.\n\nHighlights O_LIDirection of current flow is important for tDCS after-effects.\nC_LIO_LItDCS modulates excitability between two electrodes.\nC_LIO_LItDCS differentially modulates PA and AP inputs into M1.\nC_LI\n\nAbbreviations\n\nFundingThis research did not receive any specific grant from funding agencies in the public, commercial, or not-for-profit sectors.

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bioRxiv2017

Non-invasive laminar inference with MEG: Comparison of methods and source inversion algorithms

Magnetoencephalography (MEG) is a direct measure of neuronal current flow; its anatomical resolution is therefore not constrained by physiology but rather by data quality and the models used to explain these data. Recent simulation work has shown that it is possible to distinguish between signals arising in the deep and superficial cortical laminae given accurate knowledge of these surfaces with respect to the MEG sensors. This previous work has focused around a single inversion scheme (multiple sparse priors) and a single global parametric fit metric (free energy). In this paper we use several different source inversion algorithms and both local and global, as well as parametric and non-parametric fit metrics in order to demonstrate the robustness of the discrimination between layers. We find that only algorithms with some sparsity constraint can successfully be used to make laminar discrimination. Importantly, local t-statistics, global cross-validation and free energy all provide robust and mutually corroborating metrics of fit. We show that discrimination accuracy is affected by patch size estimates, cortical surface features, and lead field strength, which suggests several possible future improvements to this technique. This study demonstrates the possibility of determining the laminar origin of MEG sensor activity, and thus directly testing theories of human cognition that involve laminar- and frequency- specific mechanisms. This possibility can now be achieved using recent developments in high precision MEG, most notably the use of subject-specific head-casts, which allow for significant increases in data quality and therefore anatomically precise MEG recordings.

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bioRxiv2017

Reward and punishment enhance motor adaptation in stroke

The effects of motor learning, such as motor adaptation, in stroke rehabilitation are often transient, thus mandating approaches that enhance the amount of learning and retention. Previously, we showed in young individuals that reward-and punishment-feedback have dissociable effects on motor adaptation, with punishment improving adaptation and reward enhancing retention. If these findings were able to generalise to stroke patients, they would provide a way to optimize motor learning in these patients. Therefore, we tested this in 45 chronic stroke patients allocated in three groups. Patients performed reaching movements with their paretic arm with a robotic manipulandum. After training (day 1), day 2 involved adapting to a novel force-field. During this adaptation phase, patients received performance-based feedback according to the group they were allocated: reward, punishment or no feedback (neutral). On day 3, patients readapted to the force-field but all groups now received neutral feedback. All patients adapted, with reward and punishment groups displaying greater adaptation and readaptation than the neutral group, irrespective of demographic, cognitive or functional differences. Remarkably, the reward and punishment groups adapted to similar degree as healthy controls. Finally, the reward group showed greater retention. This study provides, for the first time, evidence that reward and punishment can enhance motor adaptation in stroke patients. Further research on reinforcement-based motor learning regimes is warranted to translate these promising results into clinical practice and improve motor rehabilitation outcomes in stroke patients.

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